The increasing complexity of production processes, fluctuating energy costs, and the requirements of the Energy Efficiency Act (EnEfG) pose significant challenges for vehicle manufacturing. Based on Model Predictive Control (MPC), IAV offers a solution for optimization-based supervisory control of production facilities.

Significant Reduction in Energy Consumption

Unlike traditional control approaches that primarily react to past data, MPC enables proactive control by predicting future system behavior. A key advantage is the intelligent use of the plant's storage capabilities, such as thermal inertia of processes or buffers in material flows. This predictive use of storage capacities smooths peak loads, minimizes idle times, and sustainably reduces overall energy consumption without compromising production goals or quality requirements.

Dynamic and Predictive Plant Control

The optimization-based supervisory control is based on a dynamic model of the production plant, considering energy sources, consumers, and energy storage. The MPC approach integrates forecasts of external energy and heat input due to weather conditions, fluctuating energy prices, and expected material inventory into the operational strategy. This strategy enables energy-optimal production while adhering to plant-compatible performance in a real-time capable supervisory plant control.

"In the research project 'Energy Efficient Building Framework' (EEBF), which deals with the overarching control of energy supply systems in residential areas, we applied energy-optimized operational management. The result: the predictive use of energy storage and the optimization of heat pump operation achieved up to 30 percent energy savings," explains Dr. Manus Thiel, responsible head of energy-optimized operational management. The generic methodology and toolchain have already been successfully used in production facilities.

Our expert on the topic

Dr. Manus Thiel
manus.thiel@iav.de
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